Depending on who you ask, AI and automation will either destroy jobs or create new ones. In reality, a greater push toward automation will probably both kill and create jobs — human workers will become redundant in certain spheres, sure, but many new roles will likely crop up. A report last year from PA Consulting, titled “People and machines: From hype to reality,” supports this assertion, predicting that AI and automation will lead to a net gain in job numbers. This is pretty much in line with findings from the Organization for Economic Co-operation and Development (OECD), a pan-governmental economic body spanning 36 member countries, which noted that “employment in total may continue to rise” even if automation disrupts specific industries.
Automation has gained increased attention amid the great social distancing experiment sparked by COVID-19. But it’s too early to say whether the pandemic will expedite automation across all industries. Recent LinkedIn data suggests AI hiringslowed during the crisis, but there are plenty of cases where automation could help people adhere to social distancing protocols — from robot baristas and cleaners to commercial drones.
Of course, any discussion about automation invariably raises the question of what it means for jobs.
Humans in the loop
As we’re still in the early stages of a broader shift to AI and automation, it’s not easy to fully envisage what new jobs could crop up — and which will be lost.
Slamcore is a London-based startup pushing to commercialize AI algorithms that help robots gain situational awareness from sensor data. Slamcore cofounder and CEO Owen Nicholson says we only have to look at some of today’s jobs to realize how difficult it can be to forecast the future.
“Contrary to some beliefs, I see robots as creating vast amounts of new jobs in the future,” he said. “Just like 50 years ago a website designer, vlogger, or database architect were not things, over the next 50 years we will see many new types of job emerge.”
Nicholson cites robot pilots as an example.
“Ubiquitous, truly autonomous robots are still a long way from reality, so with semi-autonomous capabilities with humans in the loop, we can achieve much better performance overall and generate a brand-new job sector,” he added.
There’s a growing consensus that humans will work in conjunction with robots, performing complementary roles that play to their respective strengths.
San Diego-based Brain Corp recently locked down $36 million to “help meet the growing demand for autonomous mobile robots (AMRs)” across industries affected by the pandemic — from health care to retail. Brain Corp is the company behind BrainOS, an operating system that integrates with hardware and sensors and serves as the “brains” for delivery robots used in warehouses, factories, and retail stores. BrainOS also powers self-driving floor cleaners that assist human workers. The machines come equipped with a range of sensors, including lidar and 3D time-of-flight (ToF) sensors, to self-navigate in dynamic environments.
Brain Corp said demand for BrainOS-powered cleaning robots has surged amid the COVID-19 crisis, with retail usage growing 24% in April 2020 alone. “A significant percentage of this uptick — 68% — is occurring during daytime hours, showing that businesses are cleaning more frequently and operating the technology during peak times,” Brain Corp executive Michel Spruijt told VentureBeat.
The robots generate a significant amount of performance data, which is automatically compiled into reports that need to be interpreted, assessed, and analyzed to improve operation and fleet performance. While much of this work could be incorporated into existing roles, such tasks may eventually require dedicated employees, leading to the creation of new jobs.
“Managers can view the routes being cleaned, take a look at quantitative metrics such as run time and task frequency, and receive notifications around diagnostics and relevant software updates,” Spruijt said. “An understanding of these reports and how to successfully interpret and apply this data will be imperative in order to improve store operations using automated technologies.”
The robots are typically trained to follow routes through a “teach and repeat” method, with human workers guiding them along a cleaning route and making adjustments if the environment changes. As Spruijt is quick to point out, this process “proactively includes humans.”
“The robot is not a functional robot without the human,” he said.
Additional new jobs could include maintenance workers to ensure the AMRs are functioning properly.
“The process of physically building a robot and successfully maintaining it in the field requires a set of new or enhanced skills, which are likely to increase alongside adoption of AMRs,” Spruijt said. “As manufacturing lines start to ramp up robot production, [skill sets such as] tooling, light manufacturing, and familiarity with new hardware like touchscreens and lidars will be necessary. Once in the field, service providers with applied knowledge around robot maintenance and deployment are also important in ensuring success.”
Humans and robots have distinct strengths and weaknesses, which is why a human-in-the-loop model makes sense for companies embracing automation. Veo Roboticsis a Waltham, Massachusetts-based startup that uses computer vision and 3D sensingto give industrial robots greater perception. Its Veo FreeMove system, which is due to launch next year, is designed to help manufacturers coordinate the best attributes of robots and humans, meaning it’s neither completely manual nor completely automated.
“What Veo does is enable a middle path, one where human workers with their flexibility, ingenuity, and dexterity can do the parts that humans are good at, while robots with their tirelessness and strength can help them by positioning parts or performing other elements of the process that are hard for the human worker,” Veo Robotics CEO and founder Patrick Sobalvarro explained. “It’s much quicker and cheaper to set up a work cell like this than to try to completely automate it because the human worker is able to do exactly the parts that are so hard to do automatically since they involve dexterity, sensing, and judgment.”
“This means skilled welders will spend more time welding and less time fixturing, and quality technicians will spend more time measuring and less time moving parts around,” Sobalvarro added. “Everyone will be more comfortable and get more products built.”
Source: Venture Beat